It was a topic I used as a focal point in my presentation about PR measurement and how it’s getting smarter partly through automation that captured close attention from the 50+ PR pros in the audience at a CIPR event in London last week.

Content that is based on data and analytical information will be turned into natural language writing by technologies that can proactively assemble and deliver information through automated composition engines. Content currently written by people – such as shareholder reports, legal documents, market reports, press releases and white papers – are prime candidates for these tools.

The context in which I talked about this was in how so many business processes are rapidly changing and evolving – literally in front of our eyes – as our own behaviours as human beings continue to shift (willingly as well as not so willingly) as smart machines develop more abilities to perform tasks and carry out work that previously was the domain of people. Much of this big shift is hugely beneficial to us, removing drudgery from mundaneness and converting routine to utility so that we can focus on truly valuable work.

The bigger picture, of course, is all about worries and concerns that technology is responsible for machines that are usurping our jobs that will lead to mass layoffs and more unemployment. You only need to Google the phrase “is my job at risk” to get an idea of who’s saying what about this complex topic.

Frankly, I wouldn’t rest on any laurels with any such assessment as many of the changes we already see around us will impact us in two to five years, with others within 10 years never mind 20. Take a look at the most recent Gartner Hype Cycle for Emerging Technologies 2015 to see some evidence.

In particular, note where “advanced analytics with self-service delivery” sits in the cycle – currently at the peak of inflated expectations, as are “smart advisors” (approaching the peak), “machine learning” (beginning the slide down) and “natural-language question answering” (well into the slide). Note, too, where Gartner sees such emerging tech in terms of how long each is predicted to take to reach its plateau of productvity – up to 10 years in some cases. And note two very interesting emerging technologies – “people-literate technology” and “virtual personal assistants” – that are just beginning to climb from their innovation trigger.

My point here is that we are already seeing such emerging tech in the workplace that, even in the early stages of innovation and use cases, show huge promise. Take virtual personal assistants, for instance, which I spoke about in the IBM context (disclosure: since January 2016, I work for IBM) of cognitive personal assistants.

In Gartner’s words:

A virtual personal assistant (VPA) performs some of the functions of a human personal assistant. With the user’s permission, it:

Observes user content and behavior.

Builds and maintains data models (from which it draws inferences about people, content and contexts).

Predicts users’ needs.

Builds trust.

Acts autonomously on the user’s behalf.

VPAs make everyday tasks easier (by prioritizing emails, for example), and its users generally more effective (by highlighting the most important content and interactions).

Call them VPAs or CPAs, I see the real value of such technology to individuals and organizations as true enablers of the reality of connectivity where they release the power of people to explode the benefits of dynamic outcomes rather than the processes of them. The destinations not the journeys, ones that involve people and machines together.

IBM has been working on this aspect of machine learning for some time with IBM Watson and as part of developing IBM Verse, among other things. I heard quite a bit about it at IBM Connect 2016 in Orlando, Florida, a few weeks ago; read what Constellation Research analyst Alan Lepofsky has to say about it.

Although the CIPR event in London that I spoke at was all about PR measurement, it seems very clear to me that how we measure the value of an activity like public relations is one where automation will be of real benefit. It makes complete sense to have a machine analyze a bunch of big data to, say, summarize the findings of a campaign or event that brought in results from news articles, research reports, social media posts, enterprise systems data and more – a diverse mass of unstructured data, in other words – quicker, at greater depth, and at scale that would be comparatively challenging time- and money-wise done the traditional way, ie, by people using rudimentary (by comparison) methods and tools.

We need to be way ahead of just social media listening and pre-defined dashboards. My presentation explored that a little, too, where I talked about where we need to be now – review the deck I used for the full detail.

People will add the greatest value when they get their hands on the machine-processed data from which they can model and glean actionable insights, some of which will be suggested and recommended by your virtual/cognitive personal assistant. In time, your CPA may well do more of the insights-gleaning than you especially as you gain confidence and trust in its abilities as it learns over time.

However you see this, and my speculations on where we’re going, what Gartner calls “robo writers” is a visible part of what’s changing in communication. The notion of machines writing texts is very real already as the Associated Press will testify.

Coincidentally, the launch issue of Influence, the new quarterly print magazine from the CIPR that’s just come out, has a feature on “robotic journalism” starting on page 7 referencing what the AP is doing that I saw when I picked up a copy at CIPR HQ last week.

[…] his work with IBM and specifically using their native Watson Analytics tool. He talk was titled Cognitive PR and to me it was about using a computer in about as clever as is reasonable to help you measure and […]